Titlebook: Soft Computing for Problem Solving; Proceedings of the S Manoj Thakur,Samar Agnihotri,Atulya K. Nagar Conference proceedings 2023 The Edito

prosperity

A Deep Neural Model CNN-LSTM Network for Automated Sleep Staging Based on a Single-Channel EEG Sign data exists, which has been solved in the proposed method. In addition, the overall accuracy of the proposed method was superior to those of the latest techniques based on Sleep-EDF. Hence eradicating the tedious work of sleep staging classification required by professionals. The proposed model hel

描述

,Autoencoder-Based Deep Neural Architecture for Epileptic Seizures Classification,ins a recognition accuracy of 92.47% on this task. Additionally, a relative study has been carried out with other standard neural models, specifically, deep neural networks (DNN), and CNN. Few machine learning models, namely, logistic regression (LR),random forest (RF), and K-Nearest Neighbors (KNN)